Multiperspectivity in online news: An analysis of how reading behaviour is affected by viewpoint diverse news recommendations and how they are presented
Loading...
URL
Journal Title
Journal ISSN
Volume Title
Perustieteiden korkeakoulu |
Master's thesis
Unless otherwise stated, all rights belong to the author. You may download, display and print this publication for Your own personal use. Commercial use is prohibited.
Authors
Date
2020-10-20
Department
Major/Subject
Cloud Computing and Services
Mcode
SCI3081
Degree programme
Master's Programme in ICT Innovation
Language
en
Pages
133+7
Series
Abstract
Previous research on diversity in recommender systems define diversity as the opposite of similarity and propose methods that are based on topic diversity. Diversity in news media, however, is understood as multiperspectivity and scholars generally agree that fostering diversity is the key responsibility of the press in a democratic society. Therefore, a novel viewpoint diversification method was developed, based on the reranking of recommendation lists within the topic using framing aspects. Among other results, an offline evaluation indicated that the proposed method is capable of enhancing the viewpoint diversity of recommendation lists according to a metric from literature. However, to truly enable multiperspectivity in automatic online news environments, users should also be willing to consume viewpoint diverse news recommendation. Therefore, an online study was conducted, assessing how viewpoint diverse recommendations and their presentation characteristics affect the reading behaviour of Blendle users. During a two-week experiment, two groups of 1038 users were presented a set of three recommendations below the content of two articles every day. Thereby, one group received recommendations based on relevance to the original article, while the other group received viewpoint diverse recommendations. Three implicit and one explicit measure of the reading behaviour were analysed. Additionally, the influence of the presentation characteristics of the recommendation on the reading behaviour was analysed. Generally, no major differences were found in the reading behaviour of both user groups. Only the results of the click-through rate calculated per recommendation set indicated a significant difference of $6.5\%$ to the advantage of the baseline users. For the other measures of the reading behaviour, no significant differences were found between the baseline and diverse users. However, the results do show that multiple presentation characteristics have a significant influence on the reading behaviour. Therefore, these results suggest that future research on how recommendation can be presented is just as important as novel viewpoint diversification methods to truly achieve multiperspectivity in automated online news environments.Description
Supervisor
Tintarev, NavaThesis advisor
Inel, OanaOosterman, Jasper
Keywords
recommender systems, viewpoint diversity, online news media, natural language processing